Unsupervised Binning

Unsupervised Binning is a metagenome binning method that clusters genomic fragments into putative microbial genomes without relying on prior training data or labeled reference sequences, distinguishing itself by leveraging inherent sequence composition and abundance patterns in an unsupervised machine learning framework.

16

Publications

1.2K

Citations

59

Authors

27

Institutions

Publications per year

2017–2026

6

Authors

59

  1. FY
    Francis Y. L. Chin

    University of Hong Kong, Hong Kong SAR China

    3 publications · 300 citations

    3

    h-index

  2. HC
    Henry C. M. Leung

    University of Hong Kong, Hong Kong SAR China

    3 publications · 300 citations

    3

    h-index

  3. SM
    Siu Ming Yiu

    University of Hong Kong, Hong Kong SAR China

    2 publications · 216 citations

    2

    h-index

  4. BY
    Bin Yang

    Northwest A&F University, China

    2 publications · 138 citations

    2

    h-index

  5. ST
    Sen‐Lin Tang

    Biodiversity Research Center, Academia Sinica, Taiwan

    2 publications · 112 citations

    2

    h-index

1–5 of 59

Venues

  1. BMC Bioinformatics

    5 publications · 385 citations

    5

    h-index

  2. Bioinformatics

    3 publications · 311 citations

    3

    h-index

  3. Aquatic Toxicology

    1 publications · 44 citations

    1

    h-index

  4. Journal of Computational Biology

    1 publications · 70 citations

    1

    h-index

  5. 1

    h-index

1–5